The present invention relates generally to computed tomography (CT) scanners and more specifically to a target detection apparatus and method in a baggage scanning system which utilizes CT technology.
Various X-ray baggage scanning systems are known for detecting the presence of explosives and other prohibited items in baggage or luggage prior to loading the baggage onto a commercial aircraft. Since many explosive materials may be characterized by a range of densities differentiable from that of other items typically found in baggage, explosives are generally amenable to detection by X-ray equipment. A common technique of measuring a material""s density is to expose the material to X-rays and to measure the amount of radiation absorbed by the material, the absorption being indicative of the density.
A system using computed tomography (CT) technology typically includes a CT scanner of the third generation type, which typically includes an X-ray source and an X-ray detector system secured to diametrically opposite sides of an annular-shaped platform or disk. The disk is rotatably mounted within a gantry support so that in operation the disk continuously rotates about a rotation axis while X-rays pass from the source through an object positioned within the opening of the disk to the detector system.
The detector system can include an array of detectors disposed as one or more rows in the shape of a circular arc having a center of curvature at the focal spot of the X-ray source, i.e., the point within the X-ray source from which the X-rays emanate. The X-ray source generates a fan-shaped beam, or fan beam, or cone beam of X-rays that emanates from the focal spot, passes through a planar imaging field, and is received by the detectors. The CT scanner includes a coordinate system defined by X-, Y- and Z-axes, wherein the axes intersect and are all normal to one another at the center of rotation of the disk as the disk rotates about the rotation axis. This center of rotation is commonly referred to as the xe2x80x9cisocenter.xe2x80x9d The Z-axis is defined by the rotation axis and the X- and Y-axes are defined by and lie within the planar imaging field. The fan beam is thus defined as the volume of space defined between a point source, i.e., the focal spot, and the receiving surfaces of the detectors of the detector array exposed to the X-ray beam. Because the dimension of the receiving surfaces of the linear array of detectors is relatively small in the Z-axis direction the fan beam is relatively thin in that direction. Each detector generates an output signal representative of the intensity of the X-rays incident on that detector. Since the X-rays are partially attenuated by all the mass in their path, the output signal generated by each detector is representative of the density of all the mass disposed in the imaging field between the X-ray source and that detector.
As the disk rotates, the detector array is periodically sampled, and for each measuring interval each of the detectors in the detector array generates an output signal representative of the density of a portion of the object being scanned during that interval. The collection of all of the output signals generated by all the detectors of the array for any measuring interval is referred to as a xe2x80x9cprojection,xe2x80x9d and the angular orientation of the disk (and the corresponding angular orientations of the X-ray source and the detector array) during generation of a projection is referred to as the xe2x80x9cprojection angle.xe2x80x9d At each projection angle, the path of the X-rays from the focal spot to each detector, called a xe2x80x9cray,xe2x80x9d increases in cross section from a point source to the receiving surface area of the detector, and thus is thought to magnify the density measurement because the receiving surface area of the detector area is larger than any cross sectional area of the object through which the ray passes.
As the disk rotates around the object being scanned, the scanner generates a plurality of projections at a corresponding plurality of projection angles. Using well known algorithms, a CT image of the object may be generated from all the projection data collected at each of the projection angles. The CT image is representative of the density of a two dimensional xe2x80x9cslicexe2x80x9d of the object through which the fan beam has passed during the rotation of the disk through the various projection angles. The resolution of the CT image is determined in part by the width of the receiving surface area of each detector in the plane of the fan beam, the width of the detector being defined herein as the dimension measured in the same direction as the width of the fan beam, while the length of the detector is defined herein as the dimension measured in a direction normal to the fan beam parallel to the rotation or Z-axis of the scanner.
Baggage scanners using CT techniques have been proposed. One approach, described in U.S. Pat. No. 5,182,764 (Peschmann et al.) and U.S. Pat. No. 5,367,552 (Peschmann et al.) (hereinafter the ""764 and ""552 patents), has been commercially developed and is referred to hereinafter as the xe2x80x9cIn Vision Machine.xe2x80x9d The In Vision Machine includes a CT scanner of the third generation type, Which typically include an X-ray source and an X-ray detector system secured respectively to diametrically opposite sides of an annular-shaped platform or disk. The disk is rotatably mounted within a gantry support so that in operation the disk continuously rotates about a rotation axis while X-rays pass from the source through an object positioned within the opening of the disk to the detector system.
One important design criterion for a baggage scanner is the speed with which the scanner can scan an item of baggage. To be of practical utility in any major airport, a baggage scanner should be capable of scanning a large number of bags at a very fast rate. One problem with the In Vision Machine is that CT scanners of the type described in the ""764 and ""552 patents take a relatively long time, e.g., from about 0.6 to about 2.0 seconds, for one revolution of the disk to generate the data for a single sliced CT image. Further, the thinner the slice of the beam through the bag for each image, the better the resolution of the image. The CT scanner should provide images of sufficient resolution to detect plastic explosives on the order of only a few millimeters thick. Therefore, to provide adequate resolution, many revolutions are required. To meet high baggage throughput rates, a conventional CT baggage scanner such as the In Vision Machine can only afford to generate a few CT images per bag. Clearly, one cannot scan the entire bag within the time allotted for a reasonably fast throughput. Generating only a few CT images per baggage items leaves most of the item unscanned and therefore does not provide scanning adequate to identify all potential threat objects in the bag, such as sheets of explosive material.
To improve throughput, the In Vision Machine uses a pre-screening process which produces a two-dimensional projection image of the entire bag from a single angle. Regions of the projection identified as potentially containing threat items can then be subjected to a fall scan or manual inspection. With this pre-screening and selective region scanning approach, the entire bag is not scanned, thus allowing potential threat items to pass through undetected. This is especially true in the case of sheet items oriented transversely to the direction of propagation of the radiation used to form the pre-screen projection and where the sheet covers a relatively large portion of the area of the bag.
It would be beneficial for the baggage scanning equipment to automatically analyze the acquired density data and determine if the data indicate the presence of any contraband items, e.g., explosives. This automatic explosive detection process should have a relatively high detection rate such that the chances of missing an explosive in a bag are small. At the same time, the false alarm rate of the system should be relatively low to substantially reduce or eliminate false alarms on innocuous items. Because of practical considerations of baggage throughput at large commercial airports, a high false alarm rate could reduce system performance speed to a prohibitively low rate. Also, it would be beneficial to implement a system which could distinguish among the different types of explosive, e.g., powders, bulks, sheets, etc., such that a detected threat can be more accurately characterized.
In the assignee""s CT baggage scanning system as described and claimed in the U.S. patent applications listed above and incorporated herein by reference, threat items such as explosives are identified and classified in general by analyzing mass and/or density of identified objects. Voxels in CT data for a piece of baggage are associated with density values. Voxels having density values within certain predetermined ranges of density can be identified and grouped together as objects. Using voxel volumes and densities, masses of identified objects are computed and are compared to mass thresholds. Analysis of this comparison and other predetermined parameters is used to determine whether the identified object can be classified as a threat object, i.e., an explosive.
In the assignee""s system, a set of two-dimensional slices generated by the scanning system is automatically processed to locate threat objects. The processing generally includes three steps. First, each of the voxels is examined to determine if it could be part of a threat object. The main criterion used in making this determination is the density of the voxel. Next, a connected components labeling (CCL) approach is used to assemble the identified voxels into volumes. Finally, discrimination is used to determine if the assembled voxels can be classified as a threat object. The main criteria used in this discrimination step are mass and density.
As with any other automatic identification system, false alarms on innocuous items can be generated. Also, because, like all systems, the assignee""s system has an imperfect detection rate, some threat objects may not be detected, particularly where the threat objects are concealed in or near otherwise innocuous items.
The present invention is directed to an object identification and/or discrimination apparatus and method, and a CT baggage scanning system and method which use the same. The invention can be used, for example, with the CT baggage system described and claimed in the U.S. patent applications listed above and incorporated herein by reference.
In accordance with the invention, a plurality of volume elements or voxels in the CT data for a region, each of which is associated with a density value, are identified. The region can include at least a portion of the inside of a container and/or a portion of the container itself. The container can be, for example, a piece of baggage or luggage. A plurality of object volume elements in the CT data associated with an object in the region are also identified. An axis of the object is then identified. To aid in identifying the object, a two-dimensional projection of the object is generated in a plane that is associated with the identified axis of the object.
In one embodiment, the axis of the object is a principal axis of the object defined by an eigenvector associated with the object. The eigenvector is computed from a covariance matrix for spatial locations of the voxels of the object. An eigenvalue of the covariance matrix is computed, and the eigenvector that defines the principal axis of the object is the eigenvector that is associated with the determined eigenvalue. In one embodiment, the plane in which the two-dimensional projection is generated is a plane orthogonal to the eigenvector of the covariance matrix.
In one embodiment, three mutually orthogonal axes of the object are identified. These axes can be principal axes defined by eigenvectors associated with the object, which are computed from a covariance matrix of spatial locations of the voxels of the object. The eigenvectors that define the principal axes of the object are the eigenvectors associated with the eigenvalues of the covariance matrix. In one embodiment, the plane in which the two-dimensional projection is generated is a plane orthogonal to the eigenvector associated with the smallest eigenvalue of the covariance matrix, which is referred to herein as the smallest eigenvector of the convariance matrix. Because it is generated with respect to eigenvectors, the two-dimensional projection is referred to herein as an xe2x80x9ceigen projection.xe2x80x9d
In an alternative embodiment, the plane in which the two-dimensional projection is generated is not related to eigenvectors. In this embodiment, the plane of the two-dimensional projection is selected as the plane which contains the two-dimensional projection of the object with the largest area. In one embodiment, this plane is identified by searching solid angles over a hemisphere defined in the region for which the CT data have been obtained.
In accordance with the invention, the two-dimensional projection is analyzed to alter the discrimination process of the CT baggage scanning system in which it is being used. The two-dimensional projection can be used to identify the object or a class of objects to which a selected object belongs. This analysis adds a discrimination factor based on identification of objects detected in the CT data. By improving the ability to identify objects, this approach has a tendency to reduce false alarms of the system and also increase detection rate of the system.
In accordance with the invention, the two-dimensional projection is used to provide an indication of the identity or class of a detected object. The projection can be compared to shapes of various objects by any of various well-known procedures. For example, a template matching process can be applied to the two-dimensional projection to identify the object. The identification of the object can be used to alter discrimination parameters. For example, if a particularly common innocuous item is identified, discrimination parameters can be altered to more readily clear the item as a non-threat. Additionally, or alternatively, when a particular type of item is identified, the region adjacent to the item can be examined more closely to identify features which would increase the likelihood that the object would be classified as a threat. For example, the region adjacent to the object may contain an item such as an explosive detonator. In this case, discrimination parameters can be altered to allow the item to be classified as a threat. The two-dimensional projection is defined by a plurality of projection picture elements or pixels. In one embodiment, each projection pixel is assigned a density value based on the number of object voxels above or below the projection pixel in the direction perpendicular to the plane of the two-dimensional projection, which, in one embodiment, is in the direction of the principal axis of the object or the smallest eigenvector of the covariance matrix generated for the object. In one embodiment, the value assigned to a projection pixel is related to a count of the number of voxels above or below the projection pixel in that direction. In one embodiment, the contribution of each object voxel to the count for a particular projection pixel can be weighted by the density value of the object voxel. Therefore, in the two-dimensional projection, pixels formed by projecting more dense portions of the object will have greater density.
In one embodiment, as mentioned above, the two-dimensional projection can be analyzed to identify the object and/or alter one or more discrimination parameters based on the object identification associated with the two-dimensional projection. The two-dimensional projection can also be presented on a video display to permit the operator to manually identify and/or classify the object.
Further visual analysis of the object can be performed in accordance with the invention by displaying various slices through the object taken at selected angles. For example, a cross-sectional view of the object can be displayed by producing a slice image taken along a plane perpendicular to the plane in which the two-dimensional projection is generated. In many cases, this view amounts to a cross-sectional view along the long axis of the object. This can further aid in identification of the object and/or classifying the object as to whether it poses it threat.
The present invention provides an approach to processing CT data which uses two-dimensional object projections to identify, classify and/or discriminate objects. When used in a system such as a CT baggage scanning system, the invention substantially enhances the performance characteristics of the system. By adding object projection analysis to considerations of mass and density, discrimination can be improved such that false alarms on innocuous items can be substantially reduced. The detection rate, that is, the rate at which threat items are identified and classified by the system, can also be improved.
The approach of the invention reduces the dimensionality of the three-dimensional CT data acquired for the region being analyzed to two dimensions. The two-dimensional projections thus obtained are more readily analyzed to produce an object identification that can be used to enhance the performance of subsequent discrimination steps. The two-dimensional projection provides object data in which properties and features of the object are more pronounced than they would be in three-dimensional space. As such, these properties and features can be more readily used to identify objects and perform more accurate discrimination. Also, the two-dimensional data is more readily adaptable for display and manual identification than the three-dimensional data.